Skip to main content
Glama

delimit_social_daemon

Control the autonomous social discovery daemon that scans Reddit, X, and Hacker News every 15 minutes. Start, stop, or check its status.

Instructions

Control the social sensing daemon (Pro).

When to use: to start, stop, or inspect the autonomous social discovery daemon that scans Reddit/X/HN every 15 min. When NOT to use: to run a one-shot scan (use delimit_social_target) or read the inbox (delimit_notify_inbox).

Sibling contrast: delimit_social_target is one-shot; this controls the long-running daemon.

Side effects: action="start" / "stop" mutate daemon state. The daemon scans, deduplicates, and emits HTML draft emails. Calls ai.social_daemon.{start_daemon, stop_daemon, get_daemon_status}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionNo"start", "stop", or "status" (default).status

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Describes side effects (action='start'/'stop' mutate daemon state) and internal calls to ai.social_daemon.* methods. With no annotations, additional details about daemon behavior (scans, deduplicates, emits emails) provide good transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Multi-paragraph but every sentence adds value; front-loaded with purpose, then usage, then contrast, then side effects. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given single simple parameter, presence of output schema, and rich behavioral context in description, all necessary information is covered (purpose, usage, side effects, internal calls).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and description already documents the action parameter. Description adds no new meaning beyond enumerating values already in schema directive.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool controls the social sensing daemon (start/stop/status) and distinguishes from sibling delimit_social_target (one-shot scan). Verb+resource with specific scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly provides when to use and when NOT to use, naming alternatives (delimit_social_target, delimit_notify_inbox). Includes sibling contrast.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/delimit-ai/delimit-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server